【作者】 张静宇；

【导师】 李宝仁；

【作者基本信息】 北京工商大学 ， 数量经济学， 2010， 硕士

【摘要】 随着金融体制改革的深入,我国商业银行的经营模式和经营理念发生了很大变化。面对日益开放的金融市场和金融全球化的发展,银行经营环境也在不断变化,竞争日趋激烈。同时由于金融创新的日新月异,商业银行的业务不断多样化,风险正在不断增大。市场风险、流动性风险、利率风险、汇率风险正以更新的形式摆在银行面前,其中,信用风险是商业银行所面临的主要风险。而银行客户信用风险的存在,不仅影响了信贷资质,而且干扰了正常的市场秩序。银行和客户之间的信息不对称是其根源。为了提高我国商业银行的信贷经营管理水平,增强市场竞争能力,运用现代信息技术建立科学的客户信用评估体系是十分必要的。论文首先阐述了商业银行信用风险的相关理论,通过对影响银的行信用风险因素进行分析,明确了对银行客户进行信用评估的意义,同时介绍了评估客户信用风险的指标以及风险衡量的标准。其次,作者对比了传统信用评估方法和现代信用评估方法的优劣。根据信用风险构建原则及客户评估指标的建设情况,建立了对商业银行企业型客户的信用评估指标体系,并用主成分分析法选取了最具代表性的指标,以此得出企业综合评分来作为其后神经网络模型预测准确度的一个对比参照值。再次,作者以机械设备类上市企业的指标数据作为研究样本,采用改进的BP神经网络构建了客户信用风险评估模型。经过实证分析,结果表明该模型能够比较准确的反映出指标体系与风险度之间的映射关系,达到了预期目标。最后,作者说明了神经网络的优势以及BP算法的不足之处,以及改进的方向。更多还原

【Abstract】 With the Financial market competition’s fury, the operation mode of commercial bank in our country has changed a lot. Also because of the rapid innovation of Financing, commercial bank business has been diversified, at the same time the risk increases. Market risk、liquidity risk、interest risk and exchange rate risk appeared in a new form. Among them, credit risk is the key point to commercial bank. Client credit risk will not only influence credit aptitude, but also can disturb the market system. The root of this is Information Asymmetry between client and the banks. So, in order to increase the level of credit management, enhanced marketability of commercial banks, it’s very necessary to constitute scientific credit assessment system with modern information technology.In this paper, first introduce the theory of credit risk, analyzed the generation factor of commercial bank credit risk, explicit the signification of client credit assessment ,meanwhile present assessment index of credit risk and the reference point of it. Then, the writer compared traditional method of assessment and modern method. Constituted assessment index system of corporate client credit risk of commercial bank, based on constitution principles of credit risk , and use principal component analysis to select the most influential factors. After that, the writer use index data of machinery listed companies as the samples choose modified BP neural network model to build up client credit risk assessment model. By positive analysis, the result showed this model can reflect urozzlxoek of index system and risk more precisely, attained the expected goal. At last, the writer explained the advantage of neural network and deficiency, also the direction of further perfection.更多还原